p <- ggplot(mtcars, aes(mpg, wt)) + geom_point()
# With one variable
p + facet_grid(. ~ cyl)
p + facet_grid(cyl ~ .)
# With two variables
p + facet_grid(vs ~ am)
p + facet_grid(am ~ vs)
p + facet_grid(vs ~ am, margins=TRUE)
# To change plot order of facet grid,
# change the order of variable levels with factor()
set.seed(6809)
diamonds <- diamonds[sample(nrow(diamonds), 1000), ]
diamonds$cut <- factor(diamonds$cut,
levels = c("Ideal", "Very Good", "Fair", "Good", "Premium"))
# Repeat first example with new order
p <- ggplot(diamonds, aes(carat, ..density..)) +
geom_histogram(binwidth = 1)
p + facet_grid(. ~ cut)
g <- ggplot(mtcars, aes(mpg, wt)) +
geom_point()
g + facet_grid(. ~ vs + am)
g + facet_grid(vs + am ~ .)
# You can also use strings, which makes it a little easier
# when writing functions that generate faceting specifications
p + facet_grid("cut ~ .")
# see also ?plotmatrix for the scatterplot matrix
# If there isn't any data for a given combination, that panel
# will be empty
g + facet_grid(cyl ~ vs)
# If you combine a facetted dataset with a dataset that lacks those
# facetting variables, the data will be repeated across the missing
# combinations:
g + facet_grid(vs ~ cyl)
df <- data.frame(mpg = 22, wt = 3)
g + facet_grid(vs ~ cyl) +
geom_point(data = df, colour = "red", size = 2)
df2 <- data.frame(mpg = c(19, 22), wt = c(2,4), vs = c(0, 1))
g + facet_grid(vs ~ cyl) +
geom_point(data = df2, colour = "red", size = 2)
df3 <- data.frame(mpg = c(19, 22), wt = c(2,4), vs = c(1, 1))
g + facet_grid(vs ~ cyl) +
geom_point(data = df3, colour = "red", size = 2)
# You can also choose whether the scales should be constant
# across all panels (the default), or whether they should be allowed
# to vary
mt <- ggplot(mtcars, aes(mpg, wt, colour = factor(cyl))) +
geom_point()
mt + facet_grid(. ~ cyl, scales = "free")
# If scales and space are free, then the mapping between position
# and values in the data will be the same across all panels
mt + facet_grid(. ~ cyl, scales = "free", space = "free")
mt + facet_grid(vs ~ am, scales = "free")
mt + facet_grid(vs ~ am, scales = "free_x")
mt + facet_grid(vs ~ am, scales = "free_y")
mt + facet_grid(vs ~ am, scales = "free", space = "free")
mt + facet_grid(vs ~ am, scales = "free", space = "free_x")
mt + facet_grid(vs ~ am, scales = "free", space = "free_y")
# You may need to set your own breaks for consistent display:
mt + facet_grid(. ~ cyl, scales = "free_x", space = "free") +
scale_x_continuous(breaks = seq(10, 36, by = 2))
# Adding scale limits override free scales:
last_plot() + xlim(10, 15)
# Free scales are particularly useful for categorical variables
ggplot(mpg, aes(cty, model)) +
geom_point() +
facet_grid(manufacturer ~ ., scales = "free", space = "free")
# particularly when you reorder factor levels
mpg$model <- reorder(mpg$model, mpg$cty)
manufacturer <- reorder(mpg$manufacturer, mpg$cty)
last_plot() %+% mpg + theme(strip.text.y = element_text())
# Use as.table to to control direction of horizontal facets, TRUE by default
h <- ggplot(mtcars, aes(x = mpg, y = wt)) +
geom_point()
h + facet_grid(cyl ~ vs)
h + facet_grid(cyl ~ vs, as.table = FALSE)
# Use labeller to control facet labels, label_value is default
h + facet_grid(cyl ~ vs, labeller = label_both)
# Using label_parsed, see ?plotmath for more options
mtcars$cyl2 <- factor(mtcars$cyl, labels = c("alpha", "beta", "sqrt(x, y)"))
k <- ggplot(mtcars, aes(wt, mpg)) +
geom_point()
k + facet_grid(. ~ cyl2)
k + facet_grid(. ~ cyl2, labeller = label_parsed)
# For label_bquote the label value is x.
p <- ggplot(mtcars, aes(wt, mpg)) +
geom_point()
p + facet_grid(. ~ vs, labeller = label_bquote(alpha ^ .(x)))
p + facet_grid(. ~ vs, labeller = label_bquote(.(x) ^ .(x)))
# Margins can be specified by logically (all yes or all no) or by specific
# variables as (character) variable names
mg <- ggplot(mtcars, aes(x = mpg, y = wt)) + geom_point()
mg + facet_grid(vs + am ~ gear)
mg + facet_grid(vs + am ~ gear, margins = TRUE)
mg + facet_grid(vs + am ~ gear, margins = "am")
# when margins are made over "vs", since the facets for "am" vary
# within the values of "vs", the marginal facet for "vs" is also
# a margin over "am".
mg + facet_grid(vs + am ~ gear, margins = "vs")
mg + facet_grid(vs + am ~ gear, margins = "gear")
mg + facet_grid(vs + am ~ gear, margins = c("gear", "am"))
# The facet strips can be displayed near the axes with switch
data <- transform(mtcars,
am = factor(am, levels = 0:1, c("Automatic", "Manual")),
gear = factor(gear, levels = 3:5, labels = c("Three", "Four", "Five"))
)
p <- ggplot(data, aes(mpg, disp)) + geom_point()
p + facet_grid(am ~ gear, switch = "both") + theme_light()
# It may be more aesthetic to use a theme without boxes around
# around the strips.
p + facet_grid(am ~ gear + vs, switch = "y") + theme_minimal()
p + facet_grid(am ~ ., switch = "y") +
theme_gray() %+replace% theme(strip.background = element_blank())Run the code above in your browser using DataCamp Workspace